Optimal Delay Product Differentiation System Under the Cap-and-Trade Environment

Delayed product differentiation (DD) is a two-stage hybrid system that meets the dual demands of multiple product types and fast response times. This paper studies the optimal production planning problem for DD systems under a cap-and-trade environment. We establish a model to minimize the total cost of storage, late delivery penalties, and emission quota trading and make optimal decisions on inventory levels, emission trading quantities, and types of emission trading. Data analyses show that the introduction of carbon cap-and-trade policies can effectively optimize the optimal inventory of the DD system. The loading in the MTS and MTO stages has an asymmetric impact on the cost and emission advantages of DD. Under carbon cap-and-trade policies, DD is more available than a pure MTS system.